e-commerce

To aid a fuller understanding of the costs and benefits of these distribution strategies in diverse delivery environments, this work develops a multi-echelon last-mile distribution model using Continuous Approximation (CA) techniques. The model results suggest that traditional last-mile delivery with diesel trucks is a good fit for e-retailers delivering in dense environments with lenient temporal constraints (parcel service), a strategy that allows for demand consolidation and thus low-cost low-emission distribution.

The dataset is an Analytical Tool (.xlsm format) to model last-mile delivery and different city logistics measures in the context of e-commerce delivery.

This report discusses the project which aimed to develop an analytical framework to model urban last mile delivery, building upon the previously developed econometric behavior models that capture e-commerce demand.

As e-retailers compete with increasingly consumer-focused service, urban freight witnesses a significant increase in associated distribution costs and negative externalities including greenhouse gas emissions advancing global climate change, as well as criteria pollutant emissions worsening local air quality and thus affecting those living close to logistics clusters. Thus, the author considers the potential of e-commerce to render economically viable, environmentally efficient, and socially equitable urban goods flow, which is pertinent to understand the opportunities and challenges associated with urban freight in light of the increasingly consumer-focused e-commerce distribution.

This study investigates the opportunities and challenges associated with alternate last-mile distribution strategies for an e-retailer offering expedited service with rush delivery within strict timeframes. The authors formulated a last-mile network design (LMND) problem as a dynamic-stochastic two-echelon capacitated location routing problem with time-windows (DS-2E-C-LRP-TW) addressed with an adaptive large neighborhood search (ALNS) metaheuristic.

This work models a last-mile network design problem for an e-retailer with a capacitated two-echelon distribution structure - typical in e-retail last-mile distribution, catering to a market with a stochastic and dynamic daily customer demand requesting delivery within time-windows.